Data Architect
DATAECONOMY Inc.
Core Data Engineering & Architecture and Design and build end-to-end data pipelines (ETL/ELT) for structured and unstructured data. Develop scalable data platforms handling terabytes of data with high reliability and low latency. Strong expertise in data modeling, warehousing, and lakehouse architectures. Own data quality, lineage, governance, and observability frameworks. Hands-on experience with Spark, Hadoop, Kafka, Flink (batch + real-time processing). Build and optimize high-throughput, distributed data systems. Experience in streaming + event-driven architectures for large-scale financial data. Deep expertise in AWS / Azure / GCP (Data Lakes, Warehouses, Compute, Storage) Tools: Databricks, Snowflake, Redshift, Synapse, BigQuery. Pipeline orchestration using Airflow, Prefect, or similar frameworks. Strong coding in Python, SQL, Scala/Java Focus on performance optimization, reliability, and production-grade systems. Experience with CI/CD, DevOps, and infrastructure-as-code. Ability to design architectures and make technology decisions at scale Strong understanding of: Trade lifecycle, transactions, risk, compliance, regulatory reporting. Customer 360, payments, lending, capital markets data and Wealth Management Business. GenAI / LLM integration (RAG, embeddings, vector stores). Lead legacy-to-cloud data platform migrations. Drive data re-engineering, system decomposition, and modernization initiatives. Drive resilience, failover, and incident response frameworks. Work across engineering, data science, risk, compliance, and product teams. Ability to translate business needs (risk, reporting, revenue) into data solutions. Mentor engineers and drive engineering best practices and standards Must have: Spark, Hadoop, Kafka, Flink (batch + real-time processing),Databricks, Snowflake, Redshift, Synapse, BigQuery,Deep expertise in AWS / Azure / GCP (Data Lakes, Warehouses, Compute, Storage) #J-18808-Ljbffr DATAECONOMY Inc.
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